Applying the C++ BOOST Library in Computational Finance

Note These pages are fairly old but kept for reference. Daniel J. Duffy published books on the Boost libraries. We are offering consulting services related Boost C++ libraries, please get in touch with us on webs@bnikolic.co.uk.

This is a white-paper which Daniel J. Duffy and myself are writing on the use of the BOOST collection of libraries in computational finance. The motivation for this paper is the observation that although C++ now is the standard tool for use in production systems in the field, there are very few standard, widely used C++ libraries. BOOST is the best candidate for such a library and learning and applying to your systems is likely to give significant benefits.

The white paper is still a work in progress, but as they are completed, I will be posting below the draft sections. Any comments or enquiries welcome at the address at the bottom of the page.

• Algorithms
  • Foreach (avoiding boiler-plate iterators and foreach)
  • Accumulators (efficient incremental computation)
  • Random Number (generation of random numbers)
• Data Types and Structures
  • Tuple (modeling multiple values in one class)
  • Variant (safe, efficient, discriminated union container)
  • Pointer container (exception safe container of pointers)
  • Integer library (portable integer type selection)
• String and Text Processing
  • Lexical cast (type-safe conversion of text)
  • Xpressive advanced regular expression library
  • Tokenizer (simple splitting of strings into tokens)
  • String Algorithms Library